A/B testing! Unlike ab testing, which requires you to do crunches and planks, this one has long been a darling of the optimization obsessed.
When your marketers wanna know which website design is more engaging or which email subject line generates more newsletter opens, they run an A/B test.
The idea is dead simple: Change one element (importantly only one), split the audience evenly, and compare the metrics. Develop a theory on why the A beat the B (or the B beat the A) and then run more tests until you’ve achieved maximum results.
Sounds pretty easy, right? Well, it is. But there’s an area ripe for this type of experimentation that many companies have often overlooked: the sales process.
Sales, at its core, is both an art and a science — and for what it’s worth “A/B testing” is really just the Scientific Method with a good marketing team.
Now of course while the personal touch, communication skills, and product knowledge of a salesperson cannot be undersold (pun intended), there’s an underlying structure to the whole process that can be analyzed and optimized using the scientific method. Just as marketers refine their campaigns through constant (well, hopefully constant) experimentation, RevOps and sales leaders can greatly benefit from applying the same approach to their revenue processes.
Let’s talk about why.
A/B test your sales process: why, even?
If you’re only working off assumptions or doing things the way they’ve always been done, you might be leaving a great deal of money on the table. The sales funnel is a journey, and every touchpoint in said journey can be a point of leverage to improve conversions and close more deals.
You can make your Sales Process your competitive advantage. Through A/B testing you can tinker and tweak and truly optimize how your team is engaging with customers, and each other.
Remember, even tiny improvements at any stage of the funnel can lead to a substantial increase in your bottom line. Even better? Small improvements at various parts of your funnel have compounding benefits.
But to make those improvements, you need data-driven insights, not gut instinct.
Examples of A/B Tests Across Your Sales Funnel
Here are just a few examples of the kinds of things you can A/B test in your revenue process:
Pipeline: How does the lead qualification process influence the flow of prospects into your pipeline? Consider testing two different sets of qualification criteria. For instance, Group A might be qualified based on standard industry, company size, and role, while Group B might have an additional criterion of past purchase behavior. Monitor which group moves more smoothly through the pipeline and has a higher conversion rate.
Deal Execution: The manner and frequency of communication can greatly influence deal closure. Test different check-in intervals or content types in your follow-up emails. For example, Group A could receive a weekly check-in with a case study, while Group B gets bi-weekly check-ins with a mix of video testimonials and product updates. Which method accelerates deal closure?
Customer Expansion: For businesses with a recurring revenue model, expanding customer accounts is crucial. Here, you could test onboarding processes. Group A could receive a traditional product walkthrough while Group B gets a more interactive, hands-on training session. Track which group tends to expand their usage or upgrade their packages faster.
How to A/B Test
“When am I ever going to need to use this stuff,” your 7th grade self may have said in science class.
Well, little former you: I have great news. Now’s the time it all pays off.
Let’s look at deal execution example above. To determine which deal execution strategy leads to higher close rates and improved customer satisfaction, you’ll need to follow the scientific method.
1. Formulate Your Hypothesis
Start by identifying a specific aspect of your deal execution you believe could be optimized. For instance: "We hypothesize that utilizing a consultative selling approach (Version B) will result in a 10% higher close rate than our current direct selling approach (Version A)."
2. Define Your Metrics
You need to determine what success looks like. For deal execution, typical metrics might include:
- Close rate percentage
- Time taken to close a deal
- Customer feedback/satisfaction score post-purchase
- Stage progression and/or stage conversion rates
3. Segment Your Audience
To maintain the integrity of your new A/B test, divide your prospects into two equal and randomized groups. Important: be sure that these groups are comparable in terms of size, industry, deal size, etc.
4. Implement the Two Processes
Version A: This will be your control group where the sales team uses the current deal execution process.
Version B: This is your test group. Where the rubber meets the road. Introduce the new deal execution strategy, in this case, a consultative selling approach. This may involve more in-depth conversations with the client, understanding their pain points, and tailoring your pitch to address those specific concerns.
5. Train the Team
Make sure your sales team understands the nuances of each approach. For Version B, they might need training sessions on consultative selling techniques, understanding client needs, and positioning the product or service as a solution.
6. Monitor and Gather Data
Throughout the testing period, collect data based on the metrics you've set. This might involve using CRM tools, feedback forms, or sales analytics platforms.
7. Analyze the Results
After a set period or once enough data has been gathered, compare the performance of both groups. Did Version B outperform Version A in terms of close rate? Was there a significant difference in the time taken to close a deal? How did customer satisfaction scores compare?
8. Make Informed Decisions
If the consultative approach (Version B) proved significantly more effective, consider implementing it across the board. However, if there wasn't a clear winner or if the results were counter to the hypothesis, delve deeper to understand why.
9. Iterate and Refine
The beauty of A/B testing is that it's not a one-off process. Based on the insights from one test, you can (and should) identify other areas of the deal execution process to optimize and run subsequent tests.
What’s kept revenue teams from A/B testing process in the past?
If A/B testing is so great (and it is), why aren’t revenue teams doing it all the time?
Turns out, there have been more than a few blockers to utilizing this tool to its fullest potential..
1. Complexity of Mapping Processes: A sales process isn’t always a linear progression; it’s a multi-faceted web of touchpoints, interactions, and decisions. Traditionally, mapping out this process in detail was a Herculean task. Visualizing every nook and cranny was challenging, leading many teams to rely on approximations or simplified versions that weren't entirely reflective of reality. Can’t do that and remain scientific.
2. Difficulty in Real-time Tracking: In the past, sales leaders would implement a process and then play the waiting game. By the time data came in, the market could have shifted, or other variables might have changed, making it hard to pinpoint the efficacy of a particular process.
3. Fear of Disruption: Sales is the engine that drives revenue. With so much at stake, many RevOps teams have been hesitant to tamper with an established process, even if it’s for the sake of optimization. The thought process has often been, "If it ain’t broke, why fix it?" This mindset, though safe, can hinder innovation and the kind of continuous improvement that can only come from A/B tests.
4. Historical Time Constraints: A/B testing isn’t just about having two different processes to compare; it’s about allowing enough time for each test to run its course and generate reliable data. Previously, determining the better process might have taken months, making it a time-consuming venture that many teams were hesitant to embark on.
However, the landscape is changing…
Rattle: Your Partner in Sales Process A/B Testing
Not all tools are made equal when it comes to facilitating these kind of tests. The bottom line is that you can A/B test all you like in other capacities, but if you aren’t standardizing the way your team executes on it, you’re introducing far too many variables to rely on it.
That’s where we come in, baby!
With Rattle, RevOps can not only document and visualize their sales processes, but also set up automated workflows for seamless team execution of their A strategy, their B strategy, their Z strategy, whatever. The cherry on top: observing your team’s adherence to your processes in real-time. This provides clarity, consistency, and a foundation upon which A/B tests can truly thrive.
Our dynamic process mapping and testing tool, Atlas, allows RevOps the chance to significantly streamline those aforementioned process mapping and real-time tracking challenges, and shift from traditional, time-consuming methods to fast, data-driven decisions.
The time to determine the optimization of a process has been drastically reduced, allowing for more experimentation without the extended wait.
In the modern sales environment, where agility and adaptability are everything, it's no longer about avoiding change but embracing it with the right tools and mindset.
Final Thoughts
The sales process, much like any other part of a business, should be dynamic, adaptive, and above all, effective. By not A/B testing your revenue process, you may be adhering to methods that are good but not necessarily the best. And being the best at sales process is a distinct competitive advantage.
Now’s the time to embrace the future of data-driven sales process optimization. With tools like Rattle — actually, just Rattle — the task becomes less daunting and more of an exciting opportunity to elevate your sales game.
After all, when you can visualize, execute, and track in real-time, the possibilities are indeed endless.
